NDLI: Hardware Implementation of Real-Time Speech Recognition System Using TMS320C6713 DSP

Content Provider	IEEE Xplore Digital Library
Author	Manikandan, J. Venkataramani, B. Girish, K. Karthic, H. Siddharth, V.
Copyright Year	2011
Abstract	Continuous, real-time speech recognition is required for various mobile and hands-free applications. In this paper, hardware implementation of real-time speech recognition system is proposed using two approaches and their performances are evaluated. The first approach uses Mel Filter Banks with Mel Frequency Cepstrum Coefficients (MFCC) as feature input and the second approach uses Cochlear Filter Banks with Zero-crossings (ZC) as feature input for recognition. The features extracted from input speech are fed to multi-class Support Vector Machine (SVM) classifier for recognition. The proposed recognition systems are implemented on a Texas Instruments TMS320C6713 floating point digital signal processor for recognizing isolated digits (0-9) and their performances are compared. It is observed that the program memory required for MFCC feature extraction is 44.42% higher than that required for feature extraction using Cochlear filters. Recognition accuracies of 93.33% and 98.67% are achieved for feature inputs from Mel filter banks and Cochlear filter banks respectively. It is also observed that the computational complexity of feature extraction using cochlear filters is 1.53 times of that required for MFCC feature extraction. The recognition performance is also studied for different combinations of test and training utterances. It is found that training using 15 utterances of each digit results in best recognition accuracy. The techniques proposed here can be adapted for various other hands-free consumer applications such as washing machines, hands-free cordless and many more.
Starting Page	250
Ending Page	255
File Size	493721
Page Count	6
File Format	PDF
ISBN	9781612843278
ISSN	10639667
DOI	10.1109/VLSID.2011.12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-01-02
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filter bank Mel frequency cepstral coefficient Speech recognition Support vector machines Feature extraction Real time systems Hands-free applications Real-time Speech Recognition Feature Extraction Mel Filter Bank Cochlear Filter Bank Zero crossings MFCC DSP
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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